Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1D1122270D001342B7A476CD5A9F1EF195CE3C6EDEE060484F2A41E8D4BEADB4D2ADA53 |
|
CONTENT
ssdeep
|
96:j9EuUCArar8rnAhAhEhDzMXLhxMbyG/GvBvPKuFAvnS70XSTh0vf5S70XSTnC9AH:2N4okP6xMb3+vpf9ao9QyyR2pyVD1m |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
bdc3c63cc1cb3cc0 |
|
VISUAL
aHash
|
ff9f1f790f8f9fff |
|
VISUAL
dHash
|
38323353183c38db |
|
VISUAL
wHash
|
0f0b0f490f0f0f1f |
|
VISUAL
colorHash
|
070000001c0 |
|
VISUAL
cropResistant
|
38323353183c38db,0008303232300800,31c30d71cf373f3f |
Victim enters username and password into fake login form. Credentials are captured via JavaScript and exfiltrated to attacker's server in real-time.
Malicious code is obfuscated using 37 techniques to evade detection by security scanners and make reverse engineering more difficult.
Drainer supports multiple blockchain networks and checks for high-value tokens on each chain before executing drain operations.